1. Field of the Invention
Embodiments of the present invention generally relate to a method and apparatus for object detection and more specifically to object detection in images or a video.
2. Description of the Related Art
Object detection is a fundamental problem in computer vision. In order to analyze the behavior and motion of the objects in a scene, a key challenge is to be able to first reliably detect the objects from video data. Detecting an object involves determining the location and scale of the object.
Numerous video analytics applications are based on acquiring the position and scale of the objects in the scene. For example, object detection is a necessary step before object tracking, since the tracker has to be initialized with the location and scale of the object.
There are several reasons why this is a hard problem. In any given application, there are typically many distinct object classes of interest, e.g., people, vehicles, animals, etc. Further, instances within each object category exhibit a great deal of intra-class variations, e.g., tall vs. short person, coupe vs. sedan, etc. Additionally, there can be variations due to object pose and changes in camera viewpoint. Further, there are artifacts caused due to variations in ambient conditions such as scene illumination.
These challenges can be summarized in the following list of desiderata for an object detection algorithm:                a) Robustness to illumination changes        b) Applicability across object classes        c) View and pose independence        d) Scale independence        e) Speed and efficiency        